The AI Bubble Isn't Where You Think It Is

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Jeffrey's global head of equity strategy predicted, quote, "massive capital destruction in AI." Later, the CEO of one of the largest chip makers, Broadcom, warned that AI investors have, quote, "no clue what they're investing in." Both statements were scary because they were probably true. The straw that broke the camel's back, though, was core weave. One of the world's hottest new data center providers or neoclouts. In short, the AI company's bonds went into crisis mode. The yield on its unsecured notes exploded to 15% and the spread on its credit default swaps also skyrocketed, implying a 62% probability that the company would default in the next five years. The credit markets were screaming loud and clear. This company might be about to implode. Why were investors so worried? Simply put, the company borrowed more than it can probably afford. As D.A. Davidson's Gil Luria explained on markets last week, core weave had not only taken on $50 billion in debt, they'd done so at a 9% interest rate while generating a 1% return. That's like taking out a margin loan to buy treasuries, Gil told us. From a financial perspective, it doesn't make sense. Things seemed fine until they didn't. Thanks to memory prices and political backlash, data centers turned out to be more expensive and difficult to build than originally anticipated. Meanwhile, the number of dollars flowing into the AI ecosystem is also slowing. China is primarily responsible. Their extraordinarily cheap, open-weight models have cut AI token prices in half, forcing frontier labs like open AI to reduce their prices by up to 80%. In some, the cost to build AI is going up and the price to sell it is going down. Not good. If you follow Ed Zittren, one of our frequent markets guests, you have been waiting for this. He has been warning about the implosion of neoclouds like core weave for a long time. And while that prediction hasn't necessarily come true, the warning signs are definitely starting to show. You might assume then that the AI bubble is about to burst, and therefore that the stock market is about to crash. And I wouldn't blame you for that assumption as that is generally what happens with bubbles. But all of this depends on where you think the AI bubble actually is. And if you're like me, you're not so worried about the stock market. Not because there isn't an AI bubble, there is. But because the bubble's not in the stock market, it is hiding somewhere else. First, let me explain why the stock market isn't about to crash. In one sentence, the risks of an AI implosion are already priced in. While it's true that AI stocks have risen significantly this year, that is only because their profits have actually exploded. Meanwhile, when you look at their multiples, i.e. the premium investors are willing to pay for those earnings, you realize that valuations have actually come down. Take a video, for example, whose price to earnings multiple has fallen 48% since last year. That means that investors are worried about something. They're placing heavier discounts on every dollar of Nvidia's future cash flows because they believe that there is something unsustainable about them. On their right, data centers make up more than 90% of Nvidia's business and considering their customer concentration of AI companies as well as their rising financing costs. It's not unreasonable to think that some of their customers might drop off the map. That is a significant risk, but it is a risk that investors are also pricing. The same is true for the other major chip makers. Over the past year, Broadcom's earnings multiple has fallen 54%. Microns has fallen 56%, SK Heinex has fallen 49%. Their stocks have gone up, yes, but their valuations have not. Meanwhile, all of the neoclouds have been taken to the cleaners. Core Weave is down 52% in the past year. Irons down 53%, Cypher is down 55%. These are the quintessential hot AI names that have been on every AI skeptics watch list. But investors are mostly in agreement that their futures are highly uncertain. What about Big Tech? As I wrote over the summer, Big Tech has spent much of the year in the AI doldrums. Their multiples contracted significantly out of fears that management didn't fully understand AI. And while I understood those concerns, I also found them to be overdone. As a result, I loaded up on the two most punished names, Meta and Microsoft, and what now appears to be the bottom. Since then, my investments have returned 25% and 40% respectively. And while that is awesome for me, it also raises concerns that exuberance has once again gotten too high. My take was still okay. The average earnings multiple of Meta, Alphabet, Amazon and Microsoft, when you strip out their private investment gains is a little over 30, which is less than 10% higher than the S&P 500's average. These are no longer buys in my view, but they're not sales either. They reflect a cautious optimism that pales in comparison to the dot-com boom hysteria that resulted in Cisco trading at more than 100 times earnings. So where is the bubble then? The answer is right in front of you. The two biggest names in AI are also the most overvalued. Open AI and Anthropic plan to go public at $1.4 trillion and $2 trillion respectively. That will make them the 7th and 11th most valuable companies in the world, almost equal in value to every tech IPO of the past 45 years combined. I would be fine with this if the AI labs were bringing in hundreds of billions of dollars a year. But they're not. Quite the reverse, they're losing billions of dollars a year. And it's not clear if their business models are ever going to actually work. But didn't Anthropic just say they're profitable? No, not really. The financials offered at last week's investor day revealed that Anthropic is profitable only on a "adjusted basis". What does adjusted actually mean? No one knows. But it very likely strips out revenue sharing agreements as well as their largest expense by far, which is their training costs. I either money they need to pay to build their product. Ignoring those costs is so stupid, it almost seems felonious. It's equivalent to me inserting lifts in my shoes and saying, "I'm 6'6" but on an adjusted basis. Despite these accounting gymnastics, investors have gobbled it up. At a $2 trillion valuation, Anthropic trades at nearly 30 times its revenue run rate. We can't price it against earnings because it doesn't have any. Open AI is in the same boat at $1.4 trillion. These are the kinds of prices only luxury handbag designers can get away with. As with crypto, it only works when there is a greater fool who is willing to pay it. So how could it be that investors are so cautious about some AI companies, but so delusionally optimistic about others? The answer lies in the divide between the private markets and the public markets. Private market investors are simply different people. As private startups, open AI and Anthropic have their prices set by venture capitalists in Silicon Valley. Those people care about things like founder vision and tech talent. Meanwhile, the prices of public stocks, such as Nvidia, are set by investors on Wall Street. They care about things like margins and profits. These personality differences have led to vastly different prices. In other words, we don't have an AI bubble. We have an AI start-up bubble. What would happen to anthropic valuation if it traded in the public markets? Answer? It's valuation would be cut in half. When we apply Nvidia's current price to sales multiple to anthropic, the AI labs valuation drops to roughly $1 trillion. Do the same thing to open AI, and its valuation gets halved as well. When we examine the public versus private markets divide, we learn that anthropic and open AI have been fighting in a playpen of price discovery. The same is true of many other AI start-ups too. VC investors recently determined that thinking machines was 4 times more valuable than snap despite generating a 60th of its revenue. They priced another AI company at $32 billion despite not having a product. Private markets investors have been guzzling AI cool-aid through a beer-bong without even knowing what's in it. The good news is they won't have to reckon with the reality until these start-ups actually have to go public. The bad news is that that is about to happen now. Anthropic goes public in a month. The company has filed its prospectus and everything is reportedly ready to go. The only question is whether management has the stones to actually follow through. Once they enter the Coliseum that is the public markets, anthropic investors will find out what value truly means. Dario Amade has considered this, I assure you. He knows that start-up valuations are bullshit. He knows that VCs live in a different reality. He has built his company on a planet of polyannas who accept everything and question nothing. But he is about to exit that world and enter a much harsher one. He knows this and I guarantee you he is nervous about it. That is why I wouldn't be surprised if sometime next week we read the following headline. Anthropic, delays, IPO, sites, market, uncertainty. Because it's either that or the price must come down, and I doubt that Mr. Amade is interested in the latter. This edition of Simply Put was produced by Claire Miller and Alison Weiss, edited by Natalia Cabrera and engineered by Benjamin Spencer. The Research Associate is Dan Schellan, our design editor is Olivia Renehal, special thanks to Vivian Zhang and Rohit Bola. Thank you for listening to Simply Put by Ed Ellsson. You can find this piece and many more on Substack. Just go to EdwardElsson.substack.com.